Understanding Confidence Intervals: A spelled out guide to clarify misconceptions
A clear guide to confidence intervals, what they really mean, common misconceptions, how to calculate them, and why they matter in statistical...
Statistics
Statistics tutorials from Machine Learning Plus: hands-on guides with worked examples and code you can read, copy and run. Start with the fundamentals and work through to the applied posts in the Statistics and Math track.
2025 3
Ridge Regression as MAP Estimation – Supporting notes
Explore the elegant connection between Ridge Regression and MAP estimation. Step-by-step derivation showing why the L2 penalty equals a Gaussian...
Maximum A Posteriori (MAP) Estimation – Clearly Explained
Maximum A Posteriori (MAP) estimation is a Bayesian method for finding the most likely parameter values given observed data and prior knowledge...
2024 1
F Statistic Formula – Explained
The F statistic is used in statistical hypothesis testing to determine if there are significant differences between group means. It is most commonly...
2023 11
Correlation – Connecting the Dots, the Role of Correlation in Data Analysis
Understand intricacies of correlation with our concise guide. Explore its importance, applications, and visual insights in data analysis.
Hypothesis Testing – A Deep Dive into Hypothesis Testing, The Backbone of Statistical Inference
Explore the intricacies of hypothesis testing, a cornerstone of statistical analysis. Dive into methods, interpretations, and applications for making...
Sampling and Sampling Distributions – A Comprehensive Guide on Sampling and Sampling Distributions
Explore the fundamentals of sampling and sampling distributions in statistics. Dive deep into various sampling methods, from simple random to...
Law of Large Numbers – A Deep Dive into the World of Statistics
Understanding the Law of Large Numbers: Explore how bigger sample sizes give more accurate results and why it matters in statistics and real life.
Central Limit Theorem – A Deep Dive into Central Limit Theorem and its Significance in Statistics
Explore the Central Limit Theorem's essence in this comprehensive guide. Dive deep into its significance in statistics, understand its assumptions...
Skewness and Kurtosis – Peaks and Tails, Understanding Data Through Skewness and Kurtosis”
Unravel the secrets of data distributions with skewness and kurtosis. A concise guide to understanding data asymmetry and tail behaviors
Quantiles and Percentiles – Understanding Quantiles and Percentiles, A Deep Dive with Python Examples
Dive into quantiles vs. percentiles: their key differences, applications, and tips for data analysis. Master data segmentation in this concise guide
Measures of Dispersion – Unlocking the Variability Diving Deep into Measures of Dispersion
Dive deep into the world of statistics and measures of dispersion, from understanding its essence to its practical application using Python.
Measures of Central Tendency – A Clear Guide with Examples on Measures of Central Tendency
Uncover the essentials of Measures of Central Tendency: mean, median, and mode. A concise guide for data enthusiasts and statisticians.
Types of Data in Statistics – A Comprehensive Guide
Explore the diverse world of statistics as we break down the various types of data. From qualitative to quantitative, nominal to ratio, this...
Descriptive and Inferential Statistics – Deep Dive into Descriptive and Inferential Statistics
In statistics understanding the difference between descriptive and inferential statistics is crucial for anyone looking to make sense of data...
2021 2
Partial Correlation
Partial correlation is used to find the correlation between two variables with the effect of other influencing variables being controlled.
Chi-Square test – How to test statistical significance for categorical data?
Chi-square test is used to determine whether there is a statistically significant difference between the observed frequency and the expected...
2020 5
Brier Score – How to measure accuracy of probablistic predictions
Brier score is a evaluation metric that is used to check the goodness of a predicted probability score. This is very similar to the mean squared...
One Sample T Test – Clearly Explained with Examples | ML+
One sample T-Test tests if the mean of a given sample is statistically different from a known value (a hypothesized population mean). If it is found...
Standard Error in Statistics – Understanding the concept, formula and how to calculate
Standard error allows you to build a relationship between a sample statistic (computed from a smaller sample of the population and the population's...
Confidence Interval in Statistics – Formula and Mathematical Calculation
Confidence interval is a measure to quantify the uncertainty in an estimated statisic (like the mean) when the true population parameter is unknown.
T Test (Students T Test) – Understanding the math and how it works
T Test (Students T Test) is one of the foundational statistical tests. It is used to compare the means of two groups and determine if the difference...
2019 2
What is P-Value? – Understanding the meaning, math and methods
The p-value is a probability score used in statistical tests to establish the significance of an observed effect. Its meaning is often unclear even...
Mahalanobis Distance – Understanding the math with examples (python)
Mahalanobis distance is an effective multivariate distance metric that measures the distance between a point and a distribution. It is an extremely...
2017 1
How to implement common statistical significance tests and find the p value?
Learn the purpose, when to use and how to implement statistical significance tests (hypothesis testing) with example codes in R. How to interpret P...